The present invention relates to the field of detecting buried objects using microwaves and the subsequent excavation of detected objects. More particularly, the invention relates to apparatus for imaging, identifying and excavating metal and non-metal buried objects such as landmines, pipelines and underground cables.
The United Nations has estimated that there are more than 100 million mines distributed around the world, and they are a serious threat to life and limb long after the mines are buried during hostilities. For example, every year many people are maimed and killed by long forgotten mines that were buried in Vietnam, Cambodia, Somalia and Afghanistan. Metallic mines have typically been the easiest to detect but there are many types of non-metallic mines in use that require more advanced techniques such as ground search radar to reliably detect them. Accordingly, efforts have been and are being made to develop better apparatus and techniques for locating, identifying and removing both metallic and non-metallic mines.
Buried objects can be located using a wide variety of methods, including metal detectors and ground search radar. U.S. Pat. No. 5,452,639 to Aulenbacher, et al, discloses an apparatus and method for locating below ground munitions using magnetic sensors and ground search radar mounted on a relatively light weight, unmanned, remote-controlled vehicle, and the outputs of the sensors and radar are returned to a remote processing unit for analysis. However, once mines are located they must be removed by other means. U.S. Pat. No. 5,307,272 to Butler, et al, discloses a remotely controlled minefield detector system for detecting the presence of objects such as anti-personnel and anti-tank mines on the surface of the ground or buried just under the surface of the ground utilizing metal detector sensors and short pulse radar sensors, and the outputs of the sensors are returned to a remote processing unit for analysis. However, once mines are located they must be removed by other means.
Other patents that teach the use of ground search radar to locate objects under the surface of the ground are U.S. Pat. No. 5,712,441 to Grunewald that discloses a search apparatus that is attached to a military tank to detect electrically conductive mines and then detonate them using hollow charge explosives. The Grunewald apparatus does not attempt to remove mines unexploded. U.S. Pat. No. 5,680,048 to Wollny discloses a similar ground penetrating radar and metal detector device for detecting metallic and non-metallic objects on or below the ground surface. Once a mine is located it is marked and must be removed by other means.
The difficulty associated with measuring the echo from a buried target is it""s small magnitude relative to the transmit antenna to receive antenna breakthrough, and signals reflected from the surface. The desired target signal is often almost completely masked by unwanted clutter signals. Signal processing systems shown in the prior art attempt to remedy this problem. U.S. Pat. No. 4,906,940 to Greene, et al, discloses a pattern recognition process and apparatus which automatically extracts features in displays, images, and complex signals.
Other patents that aid in object recognition include neural network technology. U.S. Pat. No. 5,612,700 to Tucker discloses a system for extracting targets from radar signatures that include high background noise/clutter with a combination of Wavelet technology and neural networks to filter out background noise. U.S. Pat. No. 5,287,430 to Iwamoto, et al, also discloses a signal discrimination device using a neural network for discrimination of input signals such as radar reception signals. U.S. Pat. No. 5,247,584 to Krogmann, discloses a signal processing arrangement for classifying objects on the basis of signals applied to a pair of neural networks. Other resources include the following journal articles and books: Werbos, P. J. xe2x80x9cBackpropagation through time: what it does and how to do it,xe2x80x9d Porc. IEEE, Vol. 78 No. 10, October 1990. Lippman, R. P. xe2x80x9cAn introduction to computing with neural nets,xe2x80x9d IEEE ASSP Magazine April 1987. Wasserman, P. D. xe2x80x9cNeural Computing,xe2x80x9d Van Nostrand Reinhod, New York, 1989. Wasserman, P. D. xe2x80x9cAdvanced Methods in Neural Computing,xe2x80x9d Van Nostrand Reinshold, New York 1993.
Other techniques to optimize the recognition of objects include the use of knowledge-based technology where a library of data is created and compared to received signals to identify objects. For example, U.S. Pat. No. 5,793,888 to Delanoy discloses a machine learning apparatus and method for image searching utilizing knowledge-based image processing. U.S. Pat. No. 5,287,430 to Iwamoto et al discloses a neural network for discriminating input signals, such as radar reception signals, and the neural network is trained to output specific codes for respective inputs.
In summary, the prior art teaches a number of ways to detect metallic and non-metallic objects such as anti-personnel and anti-tank mines, but no way to remove the mines without exploding them or manually excavating them.
It is an object of the invention to provide an improved method and apparatus for locating, identifying and removing objects, such as land mines, on or below the surface of the ground.
It is another object of the invention to reduce radio frequency clutter caused by reflections from the ground by narrowing the electromagnetic energy beam radiated and collected by the antennas.
A further object of the invention is to identify buried objects, such as land mines, by developing a library of artificial neural network weight connections for different type land mines created during training in various soil environments, and then comparing received radar images with the library for improved object recognition.
Additional objects of the invention will become apparent to those skilled in the art upon examination of the following detailed description and drawing, or may be learned by practicing the invention.
In accordance with the teaching of the invention, apparatus and a method is taught and claimed for detecting, imaging, identifying and excavating metal and non-metal objects on or buried beneath the surface of the ground, such as metallic and dielectric land mines. A remotely controlled robotic vehicle with movable arm is disclosed, and at the end of the arm is a double spade auger, each spade of which has a waveguide antenna mounted thereon and a ground penetrating radar signal is transmitted into the ground from a first waveguide antenna mounted in one spade of the double spade auger. Signals reflected from the surface of the ground and buried objects are received by an identical waveguide antenna mounted in the opposite spade of the auger. These signals are recorded as the twin-spaded auger is mechanically scanned over the ground in two mechanical rotational states for signal polarization purposes.
The recorded continuous wave signals are inserted into an artificial neural network (ANN) processor which has been previously trained with microwave signals reflected from objects on or beneath the surface of the ground in similar soil conditions. The microwave imaging and excavator system has a processor suite comprising a first ANN, a second ANN, and a general processor for controlling the operation of the system while it images, detects and excavates buried objects. The first ANN processor generates artificial neuron outputs that are processed to image the surface of the ground. The second ANN processor generates artificial neuron outputs that are processed by the general processor to image and identify objects buried in the ground, such as land mines.
The resultant image of a detected mine is compared to a library of images in order to identify the type of buried mine. If the present task is the excavation of the buried land mine, the spades of the auger are centered over the land mine and alternately rotated clockwise and counter-clockwise to auger down and around the mine. Image processing continues as the auger is steered over the object and during the process of excavation to prevent contact with the mine detonator. When the auger spades are on either side of a buried mine they are closed to grasp the mine which is then removed from the ground for disarming and disposal.
The ANN processor is trained by operating it over different types of soils and different types of known land mines or other objects, to develop correct weighting factors for the ANN processor to utilize in detecting and imaging the land mines or other objects. Alternatively, the connection weights may be calculated based on theoretical numerical electromagnetic computations of microwave signals reflected from the surface of the ground and buried objects such as land mines.